Probability based whitelist

ABSTRACT

A system and method are disclosed for maintaining a whitelist, including: obtaining message data based on an email message sent by a user; extracting recipient information from message data; updating the whitelist using the recipient information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation and claims the priority benefit ofU.S. patent application Ser. No. 13/348,318 filed Jan. 11, 2012, nowU.S. Pat. No. 9,092,761, which is a continuation and claims the prioritybenefit of U.S. patent application Ser. No. 10/449,875 filed May 29,2003, the disclosures of which are incorporated by reference.

FIELD OF THE INVENTION

The present invention relates generally to electronic messages. Morespecifically, a method and a system for avoiding spam messages aredisclosed.

BACKGROUND OF THE INVENTION

Electronic messages have become an indispensable part of moderncommunication. Electronic messages such as email or instant messages arepopular because they are fast, easy, and have essentially no incrementalcost. Unfortunately, these advantages of electronic messages are alsoexploited by marketers who regularly send out unsolicited junk messages.The junk messages are referred to as “spam,” and spam senders arereferred to as “spammers.” Spam messages are a nuisance for users. Theyclog people's email box, waste system resources, often promotedistasteful subjects, and sometimes sponsor outright scams.

A number of message filtering systems exist for mitigating the problemscaused by spam. These systems often employ a whitelist technique, wherea list of allowable sender addresses is maintained. These senderaddresses are usually added by the user. Any messages coming from asender in the whitelist is presumed to be a good, non-spam message. Thewhitelist test works as follows in some systems: once a message isreceived, the system looks up the sender address of the message in thewhitelist. If the sender address is found in the whitelist, the messageis classified as non-spam and delivered to the intended recipient. If,however, the sender address is not found in the whitelist, the messagecannot be classified and further testing is needed to determine whetherit is spam or non-spam.

Whitelisting is a widely accepted technique since it is useful inidentifying non-spam messages, and performing a whitelist test incursrelatively low overhead on the system. The effectiveness of thewhitelist depends on the entries in the whitelist; a well-maintainedwhitelist with many entries tends to be more useful than a whitelistthat has very few entries. Since most of the systems require the user tomanually add entries to his whitelist, addresses that should be added tothe whitelist may be unintentionally left out, thereby making thewhitelist less effective. Furthermore, many users find the manualprocess of adding whitelist entries somewhat tedious, and thus desire amore automated process. Also, it may be problematic or inconvenient toupload whitelists from clients to servers on systems where emailfiltering is implemented on a server. It would be useful to have a wayto maintain a whitelist that requires less manual intervention, andimproves the effectiveness of the whitelist.

SUMMARY OF THE INVENTION

Exemplary embodiments provide a mechanism for updating hierarchicalwhitelists. In one embodiment, a message application software accessesmessage data associated with an email message sent by a sender to arecipient in a network. The message application software extracts senderinformation and recipient information from the message data and sendsthe extracted information to a server that updates a plurality ofwhitelists on the server with the extracted information. The pluralityof whitelists are associated with the sender and a group of users thatshare whitelists entries. The recipient is identified as being allowedto send e-mail messages to the sender and the group of users.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be readily understood by the followingdetailed description in conjunction with the accompanying drawings,wherein like reference numerals designate like structural elements, andin which:

FIG. 1A is a block diagram illustrating a system embodiment thatmaintains an automated whitelist.

FIG. 1B is a block diagram illustrating another system embodiment thatmaintains an automated whitelist.

FIG. 1C is a block diagram illustrating another system embodiment.

FIG. 2 is a flowchart illustrating a server process for processing aninbound message.

FIG. 3A is a flowchart illustrating a process for whitelisting arecipient, according to one embodiment.

FIG. 3B is a flowchart illustrating a process for automatically updatinga whitelist using the message tap according another embodiment.

FIG. 4 is a chart illustrating a probabilistic whitelist for a trusteduser, according to one embodiment.

FIG. 5 is a flowchart illustrating the automatic updating ofhierarchical whitelists according to an embodiment.

FIG. 6 is a flowchart illustrating a message classification processusing hierarchical whitelists and blacklists according to oneembodiment.

DETAILED DESCRIPTION

It should be appreciated that the present invention can be implementedin numerous ways, including as a process, an apparatus, a system, or acomputer readable medium such as a computer readable storage medium or acomputer network wherein program instructions are sent over optical orelectronic communication links. It should be noted that the order of thesteps of disclosed processes may be altered within the scope of theinvention.

A detailed description of one or more preferred embodiments of theinvention is provided below along with accompanying figures thatillustrate by way of example the principles of the invention. While theinvention is described in connection with such embodiments, it should beunderstood that the invention is not limited to any embodiment. On thecontrary, the scope of the invention is limited only by the appendedclaims and the invention encompasses numerous alternatives,modifications and equivalents. For the purpose of example, numerousspecific details are set forth in the following description in order toprovide a thorough understanding of the present invention. The presentinvention may be practiced according to the claims without some or allof these specific details. For the purpose of clarity, technicalmaterial that is known in the technical fields related to the inventionhas not been described in detail so that the present invention is notunnecessarily obscured.

An improved technique for maintaining a whitelist is disclosed. In thisspecification, a whitelist is used to refer to a collection of data thatcan be used to identify email messages sent by allowable senders. Insome embodiments, a system obtains message data based on an emailmessage sent by a user and extracts recipient information from themessage data. Message data refers to information pertaining to the emailmessage. It may come from a variety of sources, and can be obtainedusing techniques including intercepting incoming email messages,monitoring email activities, reading log information, reading storedemail messages, or any other appropriate technique. The whitelist isthen updated using the recipient information. In some embodiments, amessage tap is used to obtain the message data. Hierarchical and/orprobabilistic whitelists are employed in some embodiments.

As used herein, a recipient may refer to any individual, device,organization or other entity that is associated with the receiving of anemail. Recipient information refers to information pertaining to therecipient, including a person's name, an email address, a domain name,an IP address, an email server identifier or any other appropriateinformation. Similarly, the sender may refer to any individual, device,organization or other entity that is associated with the sending of anemail, and the sender information refers to any information pertainingto the sender.

FIG. 1A is a block diagram illustrating a system embodiment thatmaintains an automated whitelist. The system facilitates the emailcommunication between users on the corporate/organization network(Intranet) and other users on the Internet. The Intranet users are alsoreferred to as trusted users, since they are the ones the system aims toprotect from spam messages. The system also facilitates the emailcommunication among trusted users. Trusted users use mail clients suchas 100, 102, 104 and 106 to send outbound email messages. These messagesare sent to a message transport agent 108.

The message transport agent forwards the outbound email to either theInternet or the Intranet, depending on the location of the recipient.The message transport agent also logs the activity to a log file. Amessage tap 114 residing on the message transport agent is used toobtain message data based on email messages sent by the user. Themessage data is obtained by reading the log file that includes senderand recipient information of email messages from the trusted users. Itshould be noted that there are alternative ways to obtain the messagedata. For example, the message transport agent may send logs regardingemail messages to the network and the message tap may be configured toreceive these logs. In some embodiments, the message data is the emailmessage itself, which is intercepted or accessed by the message tap.

Sender and recipient information is then extracted from the messagedata. Generally, since most people only send messages to recipients theyknow and trust, if a sender sends a message to a recipient, therecipient is unlikely to be a spammer, and the sender should be willingto accept further messages from that recipient. Thus, message tap 114sends the extracted sender and recipient information to anti-spamgateway 112, which updates a whitelist 116. The anti-spam gateway is aserver that processes incoming messages sent from the Internet, intendedfor the protected users on the Intranet. It performs functions such asmessage classification and filtering to keep spam messages from beingdelivered to the protected users. In some embodiments, the anti-spamgateway is a part of the message transport agent. In some embodiments,each protected user has an individual whitelist that is customizable,and the sender information is used to identify whose whitelist should beupdated. By monitoring messages sent by the protected user, thewhitelist is generated automatically and independently by the server.There is no need for whitelist management to be implemented on theclient machine. This simplifies original deployment and updating of thewhitelist software. The anti-spam gateway uses the whitelist to filterany incoming message intended for a protected user on the network. Anon-spam message is delivered directly, or forwarded to the messagetransport agent and then delivered.

In some embodiments, the protected users are all trusted users andcommunication among trusted users is always allowed. For example, amessage sent by a trusted user on client 100, intended for anothertrusted user on client 102 is always considered non-spam and delivered.There are various ways to achieve this. For example, the messagetransport agent may identify that the sender and the recipient are bothtrusted users, and send the message to the recipient directly.

It should be noted that the message tap may be any appropriate softwareand/or hardware component, and may be located on the message transportagent or any other appropriate locations where message data can bedetected. FIG. 1B is a block diagram illustrating another systemembodiment that maintains an automated whitelist. In this embodiment,message tap 114 resides on a firewall 120. The firewall monitorsactivities on the network and logs these activities, including outboundemail activities from a trusted user to an Internet user. A message tapexamines the firewall log and extracts the recipient information basedon log messages pertaining to the outbound email messages. The recipientinformation is added to a whitelist 116 that resides on the anti-spamgateway 112. As noted above, an individual whitelist may be maintainedfor each sender by also noting sender address for messages. In someembodiments, a single whitelist is maintained for all protected users.

FIG. 1C is a block diagram illustrating another system embodiment. Inthis embodiment, multiple message taps 122 and 124 reside on mailclients 100 and 102, respectively. When a trusted user sends an outboundmessage via one of these mail clients, the message tap that resides onthe client intercepts this message and extracts sender and recipientinformation from the message that is being sent. The recipientinformation is added to the whitelist or set of whitelists that resideon anti-spam gateway 112.

An inbound message sent by an Internet user, intended for a trusted useris received by a server. As shown in FIGS. 1A-1C, the server is ananti-spam gateway that uses the whitelist to filter the message. FIG. 2is a flowchart illustrating a server process for processing an inboundmessage. Once the server receives a message (200), it parses the messageto obtain sender information and recipient information (202). The serverthen looks up the sender information in the recipient's whitelist (204),and implements the recipient's whitelist policy accordingly (206). Insome embodiments, the sender information of the message is compared tothe addresses in the whitelist. If the sender address is found in thewhitelist, then the sender is an allowable sender and the message ispromptly delivered. If the sender address is not found in the whitelist,the message is somewhat suspect and should be further processed by theanti-spam gateway to determine whether the message is spam or non-spam.In some embodiments, the server may maintain a collective whitelist forgroups of users in addition to individual whitelists. Users may beallowed to join groups and share whitelist entries or users may beassigned to a group (for example, their division or working group withina company) with which the user will share whitelist entries. Thecombination of individual whitelists and the shared whitelist madepossible by the server analysis of outgoing email messages gives thesystem considerable flexibility.

Since the message tap implementation may vary for different embodimentsof the system, the process for whitelisting a recipient may also vary.FIG. 3A is a flowchart illustrating a process for whitelisting arecipient, according to one embodiment. The message tap intercepts oraccesses the message to obtain message data (300). The systemconfiguration may be similar to the embodiment shown in FIG. 1C, wherethe message tap is configured to intercept outbound email messages. Insome embodiments, the message tap is configured to access an emailmessage by reading a database of sent messages. Sender information andrecipient information is then extracted from the message data (302). Thewhitelist is updated with the recipient information (304). FIG. 3B is aflowchart illustrating a process for automatically updating a whitelistusing the message tap according another embodiment. A message tapobtains message data from the message transport agent (350). In someembodiments, this is done by reading a log file generated by the messagetransport agent. In some embodiments, the information is obtained byreceiving log events sent by the message transport agent. The sender andrecipient information is extracted (352) and then updates the whitelistwith the recipient information (354). It should be noted that the senderand recipient information extraction may be performed by any appropriatecomponents of the system, including the message tap and the anti-spamprocess that maintains the whitelist.

In some embodiments, the server includes whitelists that arehierarchical. One level of the hierarchy is an individual whitelist thatis customizable for every trusted user. On another level, groups ordivisions have their own whitelists that are formed using informationcollected from individual users within the groups or divisions. Thistype of whitelist is also referred to as a collaborative whitelist. Onanother level, a corporate whitelist is used to maintain whitelistedaddresses that are applicable to all the users and groups within thecorporation or organization. A global whitelist is sometimes employed bythe list provider to allow certain addresses such as the administratorsof the service provider to be whitelisted. It should be noted thatdifferent hierarchical levels and structures may also be used.

In some embodiments, the whitelists entries are probabilistic. In otherwords, the entries in the whitelist are each given a probability ofbeing allowable. FIG. 4 is a chart illustrating a probabilisticwhitelist for a trusted user, according to one embodiment. A whitelistentry includes an email address obtained from the message data,whitelist counters for all the levels in the hierarchy, blacklistcounters for all the levels in the hierarchy, and a probability of theaddress being an allowable address. The whitelist counters and theblacklist counters are used to track how many times messages from thegiven email address have been indicated as non-spam or spam,respectively, by various members in the hierarchy. Different individualsmay disagree on whether a message is spam; for example, some users in agroup may blacklist an address while others whitelist the same address.Thus, the blacklist and whitelist counter values are taken intoconsideration for arriving at the probability of being allowable for agiven address. Rules and formulas for deriving the probability maydiffer for different embodiments. For example, the various blacklist andwhitelist counters may have different weights used in computing theprobability; there may be rules governing the relationships between thehierarchies, and the blacklist or whitelist in one hierarchy mayoverride some other hierarchy.

In the example, the first address, jane@aol.com, has been whitelistedonce by the individual user. It has not been blacklisted by anybodyelse. The resulting probability of this address being an allowableaddress is set to be 100 percent. The second address,admin@mailfrontier.com has not been flagged as either a blacklistedaddress or a whitelisted address by the individual, the group, or thecorporation. However, it has been determined to be allowable andwhitelisted once on a global level. Therefore, the probability of theaddress being allowable is also set to be 100 percent. The thirdaddress, joe@msn.com, has been determined to be the address of a spammerby some members of the group and added to the group blacklist twice, butit has also been added to the group whitelist three times by othermembers. Consequently, the probability of it being spam is calculated tobe 60 percent.

It should be noted that there are a variety of methods that areapplicable for computing the probability of the message being spam,including Bayesian Priors and thresholds. In some embodiments, theblacklist and whitelist counters for an address may be set to non-zerovalues initially. For example, the initial counter values forjane@aol.com may be set to 1 for both the blacklist and the whitelist.When its global whitelist counter is incremented, its probability ofbeing spam drops from 50% to 33%.

Although the whitelist entries in the embodiment shown are identified byemail addresses, other identifiers may also be used when appropriate. Insome embodiments, the recipient information extracted from the messagedata is the domain name. Once a domain is considered allowable and isadded to the whitelist, future messages sent by all the users from thesame domain all become allowable. Using the domain name to identifywhitelist entries provides a “looser” whitelist implementation andincreases the system's efficiency. In some embodiments, the Internetprotocol (IP) address of the recipient's domain is looked up via DomainName System (DNS). Both the IP address and the email address are used toidentify a whitelist entry, thus providing a more “strict” whitelistimplementation and reducing the chances of spam messages with a spoofedemail addresses (i.e. allowable email address but sent from thespammer's mail server) getting through.

FIG. 5 is a flowchart illustrating the automatic updating ofhierarchical whitelists according to an embodiment. A trusted user sendsa message (500). The user's whitelist is updated to include recipientinformation (502). Then, a whitelist of the group that includes thetrusted user is also updated (504). A corporate whitelist is thenupdated (506), as is the global whitelist (508). Although in theembodiment shown, after the trusted user's whitelist is updated, and allthe other whitelists in the hierarchy are updated, they are notnecessarily all updated in other embodiments. In some embodiments, onlythe group whitelist is updated and the corporate and the globalwhitelists are unaffected.

FIG. 6 is a flowchart illustrating a message classification processusing hierarchical whitelists and blacklists according to oneembodiment. The whitelists and blacklists are used to help classifymessages. Once a message is received (600), the sender's information isfirst looked up in the corporate whitelist and blacklist (602). If thesender is found to be on the blacklist, the message is classified asspam and rejected (614). If the message is found to be on the corporatewhitelist, it is classified as non-spam and delivered to the intendedrecipient on the network (612). If, however, the sender is found onneither the blacklist nor the whitelist, and a classification cannot bemade on the message, the system proceeds to check the sender informationon the group or division's whitelist and blacklist (604). If it is foundin the blacklist, the message is rejected (614). If it is found in thewhitelist, the message is delivered (612).

If a decision cannot be made because the sender information is not foundin either the blacklist or the whitelist of the group, the systemproceeds to check the individual blacklist and whitelist (606). If thesender information is found in the blacklist, then the message is againrejected. If the sender information is found in the whitelist, then themessage is delivered. If a decision cannot be made, the system proceedsto check the global blacklist and whitelist (608). The global blacklistand whitelist is a list obtained from a larger community of users thatis made available to the company. A whitelisted or blacklisted sendercauses the message to be delivered or rejected accordingly, and anindecision causes the system to make a probabilistic decision (610). Themessage is either rejected or delivered based on the probabilisticdecision. In some embodiments, additional testing is performed to helpclassify the message.

The hierarchical classification scheme enables policy to be implementedat various corporate levels. In addition, individual preferences aretaken into account. Finally, a message that is unclassifiable by thecorporation, corporate group or the individual is tested versus whateverdatabase can be obtained from a larger trusted or mostly trustedcommunity. In the embodiment described, the corporate policy and thenthe group policy supersede the individual. In other embodiments, thehierarchy may change. For example, in one embodiment, the individuallists are checked after corporate policy is enforced and the group isonly used if a decision cannot be made from the individual lists.

An improved technique for maintaining a whitelist has been disclosed.The technique obtains message data based on an email message: sent by auser, and extracts recipient information from the message data. Thewhitelist is then updated based on the recipient information. Thetechnique allows the whitelist to be automatically updated using messagedata obtained from a variety of sources, thereby making the maintenanceof whitelists less cumbersome for the users, and improve the quality andeffectiveness of the whitelists.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. It should be noted that there are many alternative waysof implementing both the process and apparatus of the present invention.Accordingly, the present embodiments are to be considered asillustrative and not restrictive, and the invention is not to be limitedto the details given herein, but may be modified within the scope andequivalents of the appended claims.

For example, some embodiments may include a computer program product formaintaining a whitelist. The computer program product may be embodied ina computer readable medium. The computer program may include computerinstructions for maintaining a whitelist.

What is claimed is:
 1. A method for maintaining a probability basedwhitelist, the method comprising: storing information regarding anaddress in memory, wherein the address is associated with a groupblacklist count and a group whitelist count, wherein the group whitelistcount corresponds to a probability that the message is not associatedwith a spammer and the group blacklist count corresponds to aprobability that the message is associated with the spammer, the groupblacklist count and the group whitelist count corresponding to ahierarchy of levels associated with a defined group and a rule governinga first weight associated with the group blacklist count and a secondweight associated with the group whitelist count; receiving a messagesent to the address over a communication network sent by a useridentified as being in the defined group; executing instructions storedin memory, wherein execution of the instructions by a processor:extracts the information regarding the address from the message,increments the group whitelist count based on the message being sent bythe user identified as being in the defined group, and calculates aprobability that the address is associated with the spammer, wherein theprobability calculated is a function of the group blacklist count, thefirst weight associated with the group blacklist count, the groupwhitelist count, and the second weight associated with the groupwhitelist count based on the rule governing the first weight with thegroup blacklist count and the second weight associated with the groupwhitelist count, wherein the calculation offsets the group blacklistcount according to the first weight and independently offsets the groupwhitelist count according to the second weight; identifies that themessage is not associated with a spammer based on the calculatedprobability according to the function of the group blacklist count, thefirst weight associated with the group blacklist count, the groupwhitelist count, and the second weight associated with the groupwhitelist count; and sending the message based on the calculatedprobability.
 2. The method of claim 1, further comprising receiving oneor more indications from one or more members of the defined groupindicating that the blacklist count should be incremented.
 3. The methodof claim 2, wherein the processor executing instructions out of thememory: re-calculates the probability that the address is associatedwith a spammer based on the one or more indications; and identifies thatthe re-calculated probability indicates that the address is associatedwith the spammer.
 4. The method of claim 3, further comprising:receiving a third message; identifying that the third message is fromthe address to at least one member of the defined group; and rejectingthe third message, wherein the rejection of the third message results inthe third message not being delivered to the at least one member of thedefined group.
 5. The method of claim 1, further comprising updating anindividual whitelist count based on the message being sent by the user.6. The method of claim 5, further comprising evaluating a message sentto the user based on the individual whitelist count and an individualblacklist count, the result being indeterminate, and wherein groupwhitelist count and the group whitelist count are subsequently used toevaluate the message sent to the user.
 7. The method of claim 1, whereinthe extracted information regarding the address includes at least one ofa name, an email address, a domain name, an Internet Protocol (IP)address, and an email server identifier.
 8. An apparatus for maintaininga probability based whitelist, the apparatus comprising: memory thatstores information regarding an address, wherein the address isassociated with a group blacklist count and a group whitelist count, andthe group whitelist count corresponds to a probability that the messageis not associated with a spammer and the group blacklist countcorresponds to a probability that the message is associated with thespammer, the group blacklist count and the group whitelist countcorresponds to a hierarchy of levels associated with a defined group anda rule governing a first weight associated with the group blacklistcount and a second weight associated with the group whitelist count; anetwork interface that receives a message sent to the address by a useridentified as being in the defined group; a processor that executesinstructions stored in memory, wherein execution of the instructions bythe processor: extracts the information regarding the address from themessage, increments the group whitelist count based on the message beingsent by the user identified as being in the defined group, andcalculates a probability that the address is associated with thespammer, wherein the probability calculated is a function of the groupblacklist count, the first weight associated with the group blacklistcount, the group whitelist count, and the second weight associated withthe group whitelist count based on the rule governing the first weightwith the group blacklist count and the second weight associated with thegroup whitelist count, wherein the calculation offsets the groupblacklist count according to the first weight and independently offsetsthe group whitelist count according to the second weight; and identifiesthat the message is not associated with a spammer based on thecalculated probability according to the function of the group blacklistcount, the first weight associated with the group blacklist count, thegroup whitelist count, and the second weight associated with the groupwhitelist count, wherein the network interface sends the message basedon the calculated probability.
 9. The apparatus of claim 8, wherein thenetwork interface further receives one or more indications from one ormore members of the defined group indicating that the blacklist countshould be incremented.
 10. The apparatus of claim 9, wherein theprocessor executes further instructions to: re-calculate the probabilitythat the address is associated with a spammer after receiving the one ormore indications that the blacklist count should be incremented; andidentify that the re-calculated probability indicates that the addressis associated with the spammer.
 11. The apparatus of claim 10, whereinthe one or more computer network interfaces receives a third message,and the processor executes further instructions to: identify that thethird message is from the address to at least one member of the definedgroup; and reject the third message, wherein the rejection of the thirdmessage results in the third message not being delivered to the at leastone member of the defined group.
 12. The apparatus of claim 8, whereinthe information regarding the address includes at least one of a name,an email address, a domain name, an Internet Protocol (IP) address, andan email server identifier.
 13. The apparatus of claim 8, wherein theprocessor executes further instructions to update an individualwhitelist count based on the message being sent by the user.
 14. Anon-transitory computer readable storage medium having embodied thereina program executable by a processor to perform a method for maintaininga probability based whitelist, the method comprising: storinginformation regarding an address in memory, wherein the address isassociated with a group blacklist count and a group whitelist count,wherein the group whitelist count corresponds to a probability that themessage is not associated with a spammer and the group blacklist countcorresponds to a probability that the message is associated with thespammer, the group blacklist count and the group whitelist countcorresponding to a hierarchy of levels associated with a defined groupand a rule governing a first weight associated with the group blacklistcount and a second weight associated with the group whitelist count;receiving a message sent to the address over a communication networksent by a user identified as being in the defined group; extracting theinformation regarding the address from the message; incrementing thegroup whitelist count based on the message being sent by the useridentified as being in the defined group; calculating a probability thatthe address is associated with Ran the spammer, wherein the probabilitycalculated is a function of the group blacklist count, the first weightassociated with the group blacklist count, the group whitelist count,and the second weight associated with the group whitelist count based onthe rule governing the first weight with the group blacklist count andthe second weight associated with the group whitelist count, wherein thecalculation offsets the group blacklist count according to the firstweight and independently offsets the group whitelist count according tothe second weight; identifying that the message is not associated with aspammer based on the calculated probability according to the function ofthe group blacklist count, the first weight associated with the groupblacklist count, the group whitelist count, and the second weightassociated with the group whitelist count; and sending the message basedon the calculated probability.
 15. The non-transitory computer readablestorage medium of claim 14, wherein the program is further executableto: re-calculate the probability that the address is associated with aspammer after receiving the one or more indications that the blacklistcount should be incremented; and identify that the re-calculatedprobability indicates that the address is associated with the spammer.16. The non-transitory computer readable storage medium of claim 15,wherein a third message is received, and the program is furtherexecutable to: identify that the third message is from the address to atleast one member of the defined group; and reject the third message,wherein the rejection of the third message results in the third messagenot being delivered to at least one member of the defined group.
 17. Thenon-transitory computer readable storage medium of claim 14, furthercomprising receiving one or more indications from one or more members ofthe defined group indicating that the blacklist count should beincremented.
 18. The non-transitory computer readable storage medium ofclaim 14, wherein the extracted information regarding the addressincludes at least one of a name, an email address, a domain name, anInternet Protocol (IP) address, and an email server identifier.
 19. Thenon-transitory computer readable storage medium of claim 14, wherein theprogram is further executable to update an individual whitelist countbased on the message being sent by the user.
 20. The non-transitorycomputer readable storage medium of claim 14, wherein the program isfurther executable to evaluate a message sent to the user based on theindividual whitelist count and an individual blacklist count, the resultbeing indeterminate, and wherein group whitelist count and the groupwhitelist count are subsequently used to evaluate the message sent tothe user.